Resource Management of Video Traffic Over Heterogeneous NOMA Networks

To exploit the power domain diversity, heterogeneous non-orthogonal multiple access (NOMA) networks improve the spectrum efficiency for Internet of Things (IoT). For video traffic transmission, we formulate a resource allocation and assignment problem as a mixed integer non-linear programming (MINLP) subject to video encoding characteristics, maximum number of accessed devices, max-min fairness criterion, and total available energy of each device. To solve the resource allocation and assignment problem over heterogeneous NOMA networks, two subproblems are formulated, i.e., a packet assignment subproblem for video traffic and a joint device allocation and power control subproblem. Firstly, the joint device allocation and power control subproblem is transformed into a bi-convex programming with successive convex approximation (SCA) method. Then, an optimal device allocation and power control solution is obtained via dual decomposition method. Finally, a heuristic packet assignment algorithm via greedy method is presented for video transmission traffic. In numerical simulation, we can see that the proposed algorithm guarantees the max-min fairness among different devices, and improves the minimum and average video transmission quality over heterogeneous NOMA networks.